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Pro-tuning: Unified Prompt Tuning for Vision Tasks 期刊论文
IEEE Transactions on Circuits and Systems for Video Technology, 2023, 卷号: 34, 期号: 6, 页码: 4653 - 4667
作者:  Xing Nie;  Bolin Ni;  Jianlong Chang;  Gaofeng Meng;  Chunlei Huo;  Shiming Xiang;  Qi Tian
Adobe PDF(2224Kb)  |  收藏  |  浏览/下载：28/8  |  提交时间：2024/06/21
Federated Learning on Multimodal Data: A Comprehensive Survey 期刊论文
Machine Intelligence Research, 2023, 卷号: 20, 期号: 4, 页码: 539-553
作者:  Yi-Ming Lin;   Yuan Gao;  Mao-Guo Gong;  Si-Jia Zhang;  Yuan-Qiao Zhang;  Zhi-Yuan Li
Adobe PDF(1253Kb)  |  收藏  |  浏览/下载：28/10  |  提交时间：2024/04/23
Federated learning, multimodal learning, heterogeneous data, edge computing, collaborative learning  
Improving metric-based few-shot learning with dynamically scaled softmax loss 期刊论文
IMAGE AND VISION COMPUTING, 2023, 卷号: 140, 页码: 15
作者:  Zhang, Yu;  Zuo, Xin;  Zheng, Xuxu;  Gao, Xiaoyong;  Wang, Bo;  Hu, Weiming
收藏  |  浏览/下载：75/0  |  提交时间：2024/02/22
Few-shot learning  Metric-based learning framework  Softmax loss improvement